Natural Language Processing

Word Sense Disambiguation

Word sense disambiguation (WSD) is the task of selecting the appropriate senses of a word in a given context. It is essence of communication in a natural language. It is motivated by its use in many crucial applications such as Information retrieval, Information extraction, Machine Translation, artof- Speech tagging, etc. Various issues like scalability, ambiguity, diversity (of languages) and evaluation pose challenges to WSD solutions.

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Sub-Lexical Modelling

The finite state transducer (FST) approach [1] has been widely used recently as an effective and flexible framework for speech systems. In this framework, a speech recognizer is represented as the composition of a series of FSTs combining various knowledge sources across sub-lexical and high-level linguistic layers.

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A Simple Rule-Based Part of Speech Tagger

Automatic part of speech tagging is an area of natural language processing where statistical techniques have been more successful than rule-based methods. In this paper, we present a simple rule-based part of speech tagger which automatically acquires its rules and tags with accuracy comparable to stochastic taggers.

This paper describes the use of a statistical structural N-gram model in the natural language generation component of a Spanish-English generation-heavy hybrid machine translation system. A structural N-gram model captures the relationship between words in a dependency representation without taking into account the overall structure at the phrase level.

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Natural Language Processing

Natural Language Processing (NLP) is the computerized approach to analyzing text that is based on both a set of theories and a set of technologies. And, being a very active area of research and development, there is not a single agreed-upon definition that would satisfy everyone, but there are some aspects, which would be part of any knowledgeable person’s definition.

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Natural Language Generation

Natural Language Generation is a subfield of Computational Linguistics and language-oriented Artificial Intelligence research devoted to studying and simulating the production of written or spoken discourse. The study of human language generation is a multidisciplinary enterprise, requiring expertise in areas of linguistics, psychology, engineering and computer science.